A new AI model replaces months of simulation with near-instant predictions, changing how spacecraft operations are prepared
Updated
April 24, 2026 10:53 AM
Northrop Grumman Stargaze serves as the mother ship for the Pegasus, an air-launched orbital rocket. PHOTO: UNSPLASH
Flexcompute, a startup that builds software to simulate real-world physics, is working with Northrop Grumman to change how space missions are prepared. Together, they have developed an AI-based system that can predict how spacecraft respond during critical manoeuvres such as docking—when one spacecraft moves in and connects with another in orbit. These steps have traditionally taken months of preparation.
At the centre of this work is a long-standing problem in space operations. When a spacecraft fires its thrusters, the exhaust plume interacts with nearby surfaces. These interactions can affect movement, temperature and stability. Because these effects are difficult to test in real conditions, engineers have relied on large volumes of computer simulations to estimate outcomes before a mission. That process is slow and resource-intensive.
The new system replaces much of that workflow with a trained AI model. Instead of running millions of simulations, the model learns patterns from physics-based data and can make predictions in seconds. It also provides a measure of uncertainty, which helps engineers understand how reliable those predictions are when making decisions.
"At Northrop Grumman, we're pioneering physics AI to accelerate design and solve complex simulation and modelling problems like plume impingement—critical for station keeping, rendezvous and space robotics. Simply put: we're pushing the boundaries of advanced space operations", said Fahad Khan, Director of AI Foundations at Northrop Grumman. "Partnering with Flexcompute and NVIDIA, we're accelerating innovation and mission timelines to deliver superior space capabilities for customers at the speed they need".
The system is built using technology from NVIDIA, which provides the computing framework behind the model. Flexcompute has adapted it to handle the specific challenges of spaceflight, including how gases expand and interact in a vacuum. The result is a tool that can simulate complex scenarios much faster while maintaining the level of accuracy needed for mission planning.
By shortening preparation time, the model changes how engineers approach spacecraft design and operations. Faster predictions mean teams can test more scenarios and adjust plans more quickly. It also helps improve fuel use and extend the lifespan of spacecraft.
"Northrop Grumman's confidence reflects what sets Flexcompute apart", said Vera Yang, President and Co-Founder of Flexcompute. "We are able to take the most accurate and scalable physics foundations and evolve them into highly trained, customized Physics AI solutions that engineers can rely on. This work shows how we are transforming the role of simulation, not just speeding it up, but expanding what engineers can confidently solve and how quickly they can act".
The collaboration points to a broader shift in how engineering problems are being handled. Instead of relying only on detailed simulations that take time to run, companies are beginning to use AI systems that can approximate those results quickly while still reflecting the underlying physics.
"The industry's most ambitious space missions now demand a level of speed and precision that traditional engineering cycles can no longer sustain", said Tim Costa, vice president and general manager of computational engineering at NVIDIA. "By integrating NVIDIA PhysicsNeMo, Northrop Grumman and Flexcompute are transforming complex simulations like plume impingement from days of compute into seconds of insight, drastically accelerating the path from mission concept to orbit".
What emerges from this work is a shift in how missions are prepared. When prediction cycles move from months to seconds, testing and decision-making can happen faster. For space operations, where timing and precision are closely linked, that change could reshape how systems are built and run.
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AutoFlight’s five-tonne Matrix bets on heavy payloads and regional range to prove the case for electric flight
Updated
March 17, 2026 1:02 AM
A multiroter flying through a blue sky. PHOTO: UNSPLASH
The nascent industry of electric vertical takeoff and landing (eVTOL) aircraft has long been defined by a specific set of limitations: small payloads, short distances and a primary focus on urban air taxis. AutoFlight, a Chinese aviation startup, recently moved to shift that narrative by unveiling "Matrix," a five-tonne aircraft that represents a significant leap in scale for electric aviation.
In a demonstration at the company’s flight test center, the Matrix completed a full transition flight—the technically demanding process of switching from vertical lift-off to forward wing-born flight and back to a vertical landing. While small-scale drones and four-seat prototypes have become increasingly common, this marks the first time an electric aircraft of this mass has successfully executed the maneuver.
The sheer scale of the Matrix places it in a different category than the "flying cars" currently being tested for hops over city traffic. With a maximum takeoff weight of 5,700 kilograms (roughly 12,500 pounds), the aircraft has the footprint of a traditional regional turboprop, boasting a 20-meter wingspan. Its size allows for configurations that the industry has previously struggled to accommodate, including a ten-seat business class cabin or a cargo hold capable of carrying 1,500 kilograms of freight.
This increased capacity is more than just a feat of engineering; it is a direct attempt to solve the financial hurdles that have plagued the sector, specifically addressing the skepticism industry analysts have often expressed regarding the economic viability of smaller eVTOLs. These critics frequently cite the high cost of operation relative to the low passenger count as a barrier to entry.
AutoFlight’s founder and CEO, Tian Yu, suggested the Matrix is a direct response to those concerns. “Matrix is not just a rising star in the aviation industry, but also an ambitious disruptor,” Yu stated. “It will eliminate the industry perception that eVTOL = short-haul, low payload and reshape the rules of eVTOL routes. Through economies of scale, it significantly reduces transportation costs per seat-kilometer and per ton-kilometer, thus revolutionizing costs and driving profitability.”
To achieve this, the aircraft utilizes a "lift and cruise" configuration. In simple terms, this means the plane uses one set of dedicated rotors to lift it off the ground like a helicopter, but once it reaches a certain speed, it uses a separate propeller to fly forward like a traditional airplane, allowing the wings to provide the lift. This design is paired with a distinctive "triplane" layout—three layers of wings—and a six-arm structure to keep the massive frame stable.
These features allow the Matrix to serve a variety of roles. For the "low-altitude economy" being promoted by Chinese regulators, the startup is offering a pure electric model with a 250-kilometer range for regional hops, alongside a hybrid-electric version capable of traveling 1,500 kilometers. The latter version, equipped with a forward-opening door to fit standard air freight containers, targets a logistics sector still heavily reliant on carbon-intensive trucking.
However, the road to commercial flight remains a steep one. Despite the successful flight demonstration, AutoFlight faces the same formidable headwinds as its competitors, such as a complex global regulatory landscape and the rigorous demands of airworthiness certification. While the Matrix validates the company's high-power propulsion, moving from a test-center demonstration to a commercial fleet will require years of safety data.
Nevertheless, the debut of the Matrix signals a maturation of the startup’s ambitions. Having previously developed smaller models for autonomous logistics and urban mobility, AutoFlight is now betting that the future of electric flight isn't just in avoiding gridlock, but in hauling the weight of regional commerce. Whether the infrastructure and regulators are ready to accommodate a five-tonne electric disruptor remains the industry's unanswered question.